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s3_bucket_create

Create a new Amazon S3 bucket for storing objects and files in AWS cloud storage.

Instructions

Create a new S3 bucket

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bucket_nameYesName of the S3 bucket to create

Implementation Reference

  • Executes the S3 bucket creation using boto3 S3 client with the provided bucket name and region from environment.
    if name == "s3_bucket_create":
        response = s3_client.create_bucket(Bucket=arguments["bucket_name"],
                                           CreateBucketConfiguration={
                                               'LocationConstraint': os.getenv("AWS_REGION") or 'us-east-1'
                                           })
  • Defines the tool schema including name, description, and input schema requiring 'bucket_name'.
    Tool(
        name="s3_bucket_create",
        description="Create a new S3 bucket",
        inputSchema={
            "type": "object",
            "properties": {
                "bucket_name": {
                    "type": "string",
                    "description": "Name of the S3 bucket to create"
                }
            },
            "required": ["bucket_name"]
        }
    ),
  • Registers the list_tools handler which returns all AWS tools including s3_bucket_create via get_aws_tools().
    async def list_tools() -> list[Tool]:
        """List available AWS tools"""
        logger.debug("Handling list_tools request")
        return get_aws_tools()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('create') but doesn't cover critical aspects like required AWS permissions, potential costs, region-specific constraints, or error handling. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's appropriately sized for a simple tool and front-loaded with the core action, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool (creating resources) with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, costs, or what happens on success/failure, which are crucial for safe and effective use in an AWS context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'bucket_name' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, such as naming conventions or constraints, so it meets the baseline for high schema coverage without extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a new S3 bucket' clearly states the action (create) and resource (S3 bucket), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'dynamodb_table_create' or explain what distinguishes an S3 bucket from other AWS resources, keeping it from a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., AWS permissions, region considerations), when not to use it (e.g., for existing buckets), or refer to sibling tools like 's3_bucket_list' for checking existing buckets first.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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